4DMulti: automated multicomponent identification at complex material interfaces
Multi4D is an end-to-end neural network framework that automates identifying multiple crystalline components in 4D-STEM images. It uses a physics-informed diffusion transformer and a rotation-invariant convolutional network to translate experimental diffraction data into deterministic maps with high accuracy, enabling data-driven discovery of material interfaces.